Display language
To modulepage Generate PDF

#40966 / #2

Seit WiSe 2022/23

English

Programming Project in Python

6

Sprekeler, Henning

unbenotet

Portfolioprüfung

Zugehörigkeit


Fakultät IV

Institut für Softwaretechnik und Theoretische Informatik

34352100 FG Modellierung kognitiver Prozesse

No information

Kontakt


MAR 5-3

Lundt, Felix

lundt@tu-berlin.de

Learning Outcomes

Students will be able to plan and develop a software project in the field of computational neuroscience, artificial intelligence or data science. In the process, they will acquire and/or deepen their knowledge in the respective field and become familiar with standard software development practices, such as version control and automated testing. Finally, they will improve their ability to present and communicate the knowledge and skills acquired during completion of a project.

Content

The topic of the project changes, and is announced at the beginning of the semester. Topics will typically be within the field of computational neuroscience, artificial intelligence or data science. See https://www.cognition.tu-berlin.de/menue/teaching/ for further details.

Module Components

Pflichtgruppe:

All Courses are mandatory.

Course NameTypeNumberCycleLanguageSWSVZ
Programming Project PythonPR3435 L 10225WiSeEnglish4

Workload and Credit Points

Programming Project Python (PR):

Workload descriptionMultiplierHoursTotal
Attendance time1.060.0h60.0h
Preparation / follow-up1.0120.0h120.0h
180.0h(~6 LP)
The Workload of the module sums up to 180.0 Hours. Therefore the module contains 6 Credits.

Description of Teaching and Learning Methods

In weekly tutorial, participants will receive an overview of concepts essential for the project, and ongoing supervision throughout the semester. Discussions among students are another integral part of the tutorials. In order to work towards a first prototype/simplified version of the project (depending on the topic), there are smaller assignments in the beginning of the semester. This also allows less experienced students to get up to speed and they can make use of the provided structure to develop their ideas for the project. In addition to developing a working software solution that successfully fulfills project requirements, they will also give two short presentations: - A proposal presentation where they summarize their exploratory research and outline their planned software architecture, as well as any technologies or theory they intend to employ. - A final presentation where they demonstrate the result of their work on their project and reflect on their progress during the semester.

Requirements for participation and examination

Desirable prerequisites for participation in the courses:

Programming skills in Python, or experience in another programming language and a willingness to quickly learn Python. Familiarity with software engineering principles, object-oriented programming and knowledge of data structures and algorithms are recommended.

Mandatory requirements for the module test application:

This module has no requirements.

Module completion

Grading

ungraded

Type of exam

Portfolio examination

Type of portfolio examination

100 Punkte insgesamt

Language

English

Test elements

NamePointsCategorieDuration/Extent
(Deliverable assessment) Software implementation of prototype30writtenSoftware submission
(Deliverable assessment) Proposal presentation10flexible~15min (presentation + questions)
(Deliverable assessment) Final software implementation40writtenSoftware submission
(Deliverable assessment) Final presentation20flexible~15min (presentation + questions)

Grading scale

At least 60 points in total needed to pass.

Test description (Module completion)

No information

Duration of the Module

The following number of semesters is estimated for taking and completing the module:
1 Semester.

This module may be commenced in the following semesters:
Wintersemester.

Maximum Number of Participants

The maximum capacity of students is 16.

Registration Procedures

Please see: https://www.cognition.tu-berlin.de/menue/teaching/

Recommended reading, Lecture notes

Lecture notes

Availability:  unavailable

 

Electronical lecture notes

Availability:  unavailable

 

Literature

Recommended literature
No recommended literature given

Assigned Degree Programs


This module is used in the following Degree Programs (new System):

Studiengang / StuPOStuPOsVerwendungenErste VerwendungLetzte Verwendung
Informatik (B. Sc.)14WiSe 2022/23SoSe 2024
Wirtschaftsinformatik (B. Sc.)28WiSe 2022/23SoSe 2024

Miscellaneous

No information